2-D Digital Predistortion (2-D-DPD) Architecture for Concurrent Dual-Band Transmitters
Why this work is in the frame
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Bibliographic record
Abstract
This paper presents a novel 2-D digital-predistortion (2-D-DPD) technique that is applicable for linearization of concurrent dual-band transmitters. This technique uses a unique way for distortion compensation and linearization of dual-band transmitters by selecting, characterizing, and applying predistortion in each band separately. Compared to conventional linearization techniques, this 2-D-DPD method requires a lower sampling rate for digital-to-analog and analog-to-digital converters. The performance of the 2-D-DPD topology is evaluated using two modulated signals, Worldwide Interoperability for Microwave Access and wideband code-division multiple-access, separated in frequency by 100 MHz. The measurement results show an adjacent channel power ratio of less than -50 dBc and a normalized mean square error of less than -40 dB.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it